Machine Learning Development Course
This course provides hands-on experience in developing machine learning models for binary classification, from data preparation to deployment and monitoring, using Python and scikit-learn.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Machine Learning Development Course teaches you how to gather, clean, and process customer data, then train, adjust, and compare binary classifiers using Python and scikit-learn. You will learn solid validation methods, business-oriented metrics, threshold choices, and model explanations, then wrap models into APIs, ensure they can be repeated, comply with privacy rules, and track performance after going live for dependable, practical results.
Elevify advantages
Develop skills
- Build strong ML pipelines: clean data, create features, and manage imbalance quickly.
- Train and adjust models: compare algorithms, fine-tune hyperparameters, select the best ones.
- Design production-ready ML APIs: save models, check inputs, and protect access.
- Evaluate models with business-focused metrics: ROC-AUC, PR-AUC, F1, and cost considerations.
- Monitor deployed models: spot drift, record experiments, and schedule retraining.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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Giulio CarloDigital Marketing Student
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